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3. COVID-19 could accelerate the decline in recreational hunting: A natural experiment from Northern Italy.

Author

Cerri, Jacopo, Musto, Carmela, Ferretti, Marco, Delogu, Mauro, Bertolino, Sandro, Martinoli, Adriano, Bisi, Francesco, Preatoni, Damiano Giovanni, Tattoni, Clara, and Apollonio, Marco

Subjects
HUNTING, WILDLIFE management, COVID-19 pandemic, OLDER people, POPULATION aging
Abstract

Although many studies highlighted the potential of COVID-19 to reshape existing models of wildlife management, empirical research on this topic has been scarce, particularly in Europe. We investigated the potential of COVID-19 pandemic to accelerate the ongoing decline in an aging population of recreational hunters in Italy. Namely, we modelled spatiotemporal trends between 2011 and 2021 in the number of recreational hunters in 50 Italian provinces with a varying incidence of COVID-19, and temporally delayed waves of infection. Compared to projections from 2011–2019 data, we detected a lower number of hunters who enrolled for the hunting season, both in 2020 (14 provinces) and in 2021 (15 provinces). The provinces with the highest incidence of COVID-19 in the Lombardy and Emilia-Romagna regions were also those experiencing the most marked decrease in hunting participation. Our findings revealed that a wildlife management system based on recreational hunting can be rapidly destabilized by epidemics and their associated public health measures, particularly when the average age of hunters is high, like in Italy. Considered the high incidence attained by COVID-19 in many European countries, where hunters are pivotal for the management of large ungulates and where they were already declining before the pandemic, our findings call for further large-scale research about the impact of COVID-19 on hunting participation. [ABSTRACT FROM AUTHOR]

Published
2024
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6. Not only seeds: a cultural ecosystem service provided by the Apennine brown bear.

Author

Tattoni, Clara, Galaverni, Marco, Pollutri, Antonio, Preatoni, Damiano G., Martinoli, Adriano, and Araña, Jorge E.

Subjects
*BROWN bear, *COST of living, *KEYSTONE species, *COST control, *VALUE (Economics), *CULTURAL values, *ECOSYSTEM services
Abstract

The unequal distribution of the costs and benefits of living with wildlife is one of the causes of human-carnivore conflicts. The existence of large carnivores is valued globally, but the costs of damages and management impacts human residents. The Apennine brown bear is endemic of central Italy and, besides its ecological value, it can attract tourists in search of nature and wilderness. The Advertising Value Equivalent of the bears' appearances in the national newspaper and on television from 2015 to 2020 was used to calculate the economic value of this flagship species as a destination image. The 11 million Euro of Advertising Value Equivalent estimated largely exceeded the amount of reimbursements sustained by the Park to manage this carnivore in the same period. This evaluation of cultural value could be used to highlight the economic benefits provided by the bear and contribute to the discussions with managers and stakeholders. [ABSTRACT FROM AUTHOR]

Published
2024
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7. Estimating canopy and stand structure in hybrid poplar plantations from multispectral UAV imagery.

Author

Romano, Elio, Brambilla, Massimo, Chianucci, Francesco, Tattoni, Clara, Puletti, Nicola, Chirici, Gherardo, Travaglini, Davide, and Giannetti, Francesca

Subjects
LEAF area index, HEMISPHERICAL photography, DIGITAL cameras, PLANT canopies, DRONE aircraft, MULTISPECTRAL imaging
Abstract

Accurate estimates of canopy structure like canopy cover (CC), Leaf Area Index (LAI), crown volume (Vcr), as well as tree and stand structure like stem volume (V_st) and basal area (G), are considered essential measures to manage poplar plantations effectively as they are correlated with the growth rate and the detection of possible stress. This research exploits the possibility of developing a precision forestry application using an unmanned aerial vehicle (UAV), terrestrial digital camera and traditional field measurements to monitor poplar plantation variables. We set up the procedure using explanatory variables from the Grey Level Co-occurrence Matrix textural metrics (Entropy, Variance, Dissimilarity and Contrast) calculated based on UAV multispectral imagery. Our results show that the GCLM texture derived by multispectral ortomosaic provides adequate explanatory variables to predict poplar plantation characteristics related to plants' canopy and stand structure. The evaluation of the models targeting the different poplar plantation variables (i.e. Vcr, G_ha, Vst_ha, CC and LAI) with the four GLCM explanatory variables (i.e. Entropy, Variance, Dissimilarity and Contrast) consistently higher or equal resulted to R² ≥0.86. [ABSTRACT FROM AUTHOR]

Published
2024
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15. PRECISIONPOP: a multi-scale monitoring system for poplar plantations integrating field, aerial and satellite remote sensing

Author

Chianucci, Francesco, primary, Giannetti, Francesca, additional, Tattoni, Clara, additional, Puletti, Nicola, additional, Giorcelli, Achille, additional, Bisaglia, Carlo, additional, Romano, Elio, additional, Brambilla, Massimo, additional, Chiarabaglio, Piermario, additional, Gennaro, Massimo, additional, d'Amico, Giovanni, additional, Francini, Saverio, additional, Mattioli, Walter, additional, Coaloa, Domenico, additional, Corona, Piermaria, additional, and Chirici, Gherardo, additional

Published
2022
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19. rasterdiv—An Information Theory tailored R package for measuring ecosystem heterogeneity from space: To the origin and back

Author

Rocchini, Duccio, Thouverai, Elisa, Marcantonio, Matteo, Iannacito, Martina, Da Re, Daniele, Torresani, Michele, Bacaro, Giovanni, Bazzichetto, Manuele, Bernardi, Alessandra, Foody, Giles M., Furrer, Reinhard, Kleijn, David, Larsen, Stefano, Lenoir, Jonathan, Malavasi, Marco, Marchetto, Elisa, Messori, Filippo, Montaghi, Alessandro, Naimi, Babak, Ricotta, Carlo, Rossini, Micol, Santi, Francesco, Santos, Maria J., Schaepman, Michael E., Schneider, Fabian D., Schuh, Leila, Silvestri, Sonia, Skidmore, Andrew K., Tattoni, Clara, Tordoni, Enrico, Vicario, Saverio, Zannini, Piero, Wegmann, Martin, and Goslee, Sarah

Subjects
Ecological Modelling, Ecology, Evolution, Behavior and Systematics
Abstract

Ecosystem heterogeneity has been widely recognized as a key ecological indicator of several ecological functions, diversity patterns and change, metapopulation dynamics, population connectivity or gene flow. In this paper, we present a new R package—rasterdiv—to calculate heterogeneity indices based on remotely sensed data. We also provide an ecological application at the landscape scale and demonstrate its power in revealing potentially hidden heterogeneity patterns. The rasterdiv package allows calculating multiple indices, robustly rooted in Information Theory, and based on reproducible open-source algorithms.

Published
2021

23. Measuring diversity from space: a global view of the free and open source rasterdiv R package under a coding perspective

Author

UCL - SST/ELI/ELIC - Earth & Climate, UCL - SST/ELI/ELIB - Biodiversity, Thouverai, Elisa, Marcantonio, Matteo, Bacaro, Giovanni, Da Re, Daniele, Iannacito, Martina, Marchetto, Elisa, Ricotta, Carlo, Tattoni, Clara, Vicario, Saverio, Rocchini, Duccio, UCL - SST/ELI/ELIC - Earth & Climate, UCL - SST/ELI/ELIB - Biodiversity, Thouverai, Elisa, Marcantonio, Matteo, Bacaro, Giovanni, Da Re, Daniele, Iannacito, Martina, Marchetto, Elisa, Ricotta, Carlo, Tattoni, Clara, Vicario, Saverio, and Rocchini, Duccio

Abstract

The variation of species diversity over space and time has been widely recognised as a key challenge in ecology. However, measuring species diversity over large areas might be difficult for logistic reasons related to both time and cost savings for sampling, as well as accessibility of remote ecosystems. In this paper, we present a new R package - rasterdiv - to calculate diversity indices based on remotely sensed data, by discussing the theory behind the developed algorithms. Obviously, measures of diversity from space should not be viewed as a replacement of in situ data on biological diversity, but they are rather complementary to existing data and approaches. In practice, they integrate available information of Earth surface properties, including aspects of functional (structural, biophysical and biochemical), taxonomic, phylogenetic and genetic diversity. Making use of the rasterdiv package can result useful in making multiple calculations based on reproducible open source algorithms, robustly rooted in Information Theory.

Published
2021

24. rasterdiv—An Information Theory tailored R package for measuring ecosystem heterogeneity from space: To the origin and back

Author

UCL - SST/ELI - Earth and Life Institute, UCL - SST/ELI/ELIC - Earth & Climate, Rocchini, Duccio, Thouverai, Elisa, Marcantonio, Matteo, Iannacito, Martina, Da Re, Daniele, Torresani, Michele, Bacaro, Giovanni, Bazzichetto, Manuele, Bernardi, Alessandra, Foody, Giles M., Furrer, Reinhard, Kleijn, David, Larsen, Stefano, Lenoir, Jonathan, Malavasi, Marco, Marchetto, Elisa, Messori, Filippo, Montaghi, Alessandro, Moudrý, Vítězslav, Naimi, Babak, Ricotta, Carlo, Rossini, Micol, Santi, Francesco, Santos, Maria J., Schaepman, Michael E., Schneider, Fabian D., Schuh, Leila, Silvestri, Sonia, Ŝímová, Petra, Skidmore, Andrew K., Tattoni, Clara, Tordoni, Enrico, Vicario, Saverio, Zannini, Piero, Wegmann, Martin, UCL - SST/ELI - Earth and Life Institute, UCL - SST/ELI/ELIC - Earth & Climate, Rocchini, Duccio, Thouverai, Elisa, Marcantonio, Matteo, Iannacito, Martina, Da Re, Daniele, Torresani, Michele, Bacaro, Giovanni, Bazzichetto, Manuele, Bernardi, Alessandra, Foody, Giles M., Furrer, Reinhard, Kleijn, David, Larsen, Stefano, Lenoir, Jonathan, Malavasi, Marco, Marchetto, Elisa, Messori, Filippo, Montaghi, Alessandro, Moudrý, Vítězslav, Naimi, Babak, Ricotta, Carlo, Rossini, Micol, Santi, Francesco, Santos, Maria J., Schaepman, Michael E., Schneider, Fabian D., Schuh, Leila, Silvestri, Sonia, Ŝímová, Petra, Skidmore, Andrew K., Tattoni, Clara, Tordoni, Enrico, Vicario, Saverio, Zannini, Piero, and Wegmann, Martin

Abstract

Ecosystem heterogeneity has been widely recognized as a key ecological indicator of several ecological functions, diversity patterns and change, metapopulation dynamics, population connectivity or gene flow. In this paper, we present a new R package—rasterdiv—to calculate heterogeneity indices based on remotely sensed data. We also provide an ecological application at the landscape scale and demonstrate its power in revealing potentially hidden heterogeneity patterns. The rasterdiv package allows calculating multiple indices, robustly rooted in Information Theory, and based on reproducible open-source algorithms.

Published
2021

26. Classificazione Object Oriented e caratterizzazione morfologica di semi di specie forestali tramite immagini fotografiche digitali

Author

Fiorentini, Claudia, Chianucci, Francesco, Ciolli, Marco, Tattoni, Clara, and Zatelli, Paolo

Subjects
Object-based Image Analysis, GRASS GIS, R language, semi di specie forestale
Abstract

e foreste di latifoglie sono caratterizzate da una produzione variabile di semi tra un anno e l’altro. Durante le annate di "pasciona" si osserva una fruttificazione molto abbondante, che si alterna ad una o più annate di fruttificazione scarsa in maniera irregolare e le cui cause sono ancora oggetto di studio. Tale variabilità influenza fortemente le dinamiche naturali di tali ecosistemi e le catene trofiche dipendenti da tale disponibilità fluttuante di seme, che comprende tra le altre numerosi specie di roditori, uccelli, e ungulati selvatici. La stima della produzione di seme in un soprassuolo forestale avviene solitamente tramite raccolta manuale e conteggio del seme durante il periodo autunno-invernale in specifici collettori (littertraps). Tale metodo ovviamente è molto oneroso in termini di tempi e costi, il che ne limita anche la sua applicazione ad ampia scala geografica. In alternativa al metodo della raccolta manuale, è stato effettuato uno studio preliminare per testare metodi speditivi per la stima della produzione di seme tramite analisi di immagini fotografiche digitali della quantità di seme caduto a terra durante il periodo autunno-invernale. In questo lavoro ci si concentra sulla parametrizzazione della classificazione ad oggetti di immagini di semi di specie forestali e sulla validazione confrontando il risultato con quello ottenuto dalla conta manuale. La ricerca e l’analisi di immagini di semi e frutti si sono finora concentrate sui semi utilizzati in agricoltura. Gli studi disponibili sono focalizzati sull’analisi della forma di semi e frutti in condizioni di laboratorio, ovvero analizzando immagini contenenti un solo tipo di seme e con sfondo artificiale ed uniforme. L’analisi e identificazione del seme da immagini a terra in soprassuoli forestali presenta maggiori complessità, dal momento che il seme caduto a terra deve essere separato da altri elementi tipicamente presenti a livello del suolo, quali fogliame, rinnovazione naturale, legno morto, lettiera, che crea un background complesso dal quale dover identificare il seme caduto a terra. In questo lavoro si è valutato il metodo Object-based Image Analysis (OBIA) con classificazione supervisionata per la quantificazione della produzione del seme da fotografie in ambiente naturale La raccolta delle immagini è stata effettuata in soprassuoli di diverse specie forestali (faggio, castagno, cerro, leccio) e con diversi trattamenti selvicolturali (ceduo, fustaia, avviamento) tramite campionamento fotografico standard condotto durante il periodo autunnale-invernale utilizzando quadrati a terra di 50 cm x 50 cm posizionati nel terreno. Sono stati determinati i valori ottimali dei parametri per la segmentazione delle immagini, e successivamente sono state classificate con metodo machine learning, sfruttando le capacità di GRASS GIS e R, combinando diversi classificatori e sistemi di voto. Il risultato ottenuto è una mappa vettoriale per ogni immagine, in cui ad ogni seme corrisponde un poligono, al quale è associata una tabella che riporta la classificazione del seme e la sua caratterizzazione morfologica (superficie, perimetro, compattezza). È stata quindi possibile la descrizione della distribuzione di ogni parametro morfologico per ogni specie. Il risultato è stato testato rispetto ad una classificazione manuale dell’immagine stessa. L’utilizzo di sistemi FOSS garantisce la riproducibilità delle analisi ed il controllo dei risultati., paolo.zatelli@unitn.it

Published
2020
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28. rasterdiv - an Information Theory tailored R package for measuring ecosystem heterogeneity from space: to the origin and back

Author

Rocchini, Duccio, primary, Thouverai, Elisa, additional, Marcantonio, Matteo, additional, Iannacito, Martina, additional, Da Re, Daniele, additional, Torresani, Michele, additional, Bacaro, Giovanni, additional, Bazzichetto, Manuele, additional, Bernardi, Alessandra, additional, Foody, Giles M., additional, Furrer, Reinhard, additional, Kleijn, David, additional, Larsen, Stefano, additional, Lenoir, Jonathan, additional, Malavasi, Marco, additional, Marchetto, Elisa, additional, Messori, Filippo, additional, Montaghi, Alessandro, additional, Moudrý, Vítězslav, additional, Naimi, Babak, additional, Ricotta, Carlo, additional, Rossini, Micol, additional, Santi, Francesco, additional, Santos, Maria J., additional, Schaepman, Michael, additional, Schneider, Fabian, additional, Schuh, Leila, additional, Silvestri, Sonia, additional, Šímová, Petra, additional, Skidmore, Andrew K., additional, Tattoni, Clara, additional, Tordoni, Enrico, additional, Vicario, Saverio, additional, Zannini, Piero, additional, and Wegmann, Martin, additional

Published
2021
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30. Effects of cumulated outdoor activity on wildlife habitat use

Author

Corradini, Andrea, primary, Randles, Matthias, additional, Pedrotti, Luca, additional, van Loon, Emiel, additional, Passoni, Gioele, additional, Oberosler, Valentina, additional, Rovero, Francesco, additional, Tattoni, Clara, additional, Ciolli, Marco, additional, and Cagnacci, Francesca, additional

Published
2021
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36. Integrated scientific synthesis and evaluation of LIFE FutureForCoppiceS project results (with Synthesis for resource managers and policy makers)

Author

Cutini, Andrea, Brunialti, Giorgio, Amici, Valerio, Bagella, Simonetta, Bertini, Giada, Caddeo, Corinne, Calderisi, Marco, Chianucci, Francesco, Ciucchi, Bruno, Corradini, Stefano, Riccioli, Francesco, Rocchini, Duccio, Roggero, Pier Paolo, Uniss, Giovanna Seddaiu, Tattoni, Clara, Gottardini, Elena, Cristofolini, Fabiana, and Salvatore, Umberto Di

Published
2019
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